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Prediction model for hyperprogressive disease in non‐small cell lung cancer treated with immune checkpoint inhibitors

BACKGROUND: Hyperprogressive disease (HPD) is a paradoxical acceleration of tumor growth after immune checkpoint inhibitor (ICI) treatment. This study aimed to identify the risk factors and to present a predictive model for HPD in patients treated with ICIs. METHODS: A total of 78 non‐small cell lun...

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Autores principales: Choi, Yong Jun, Kim, Taehee, Kim, Eun Young, Lee, Sang Hoon, Kwon, Do Sun, Chang, Yoon Soo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons Australia, Ltd 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7529559/
https://www.ncbi.nlm.nih.gov/pubmed/32779394
http://dx.doi.org/10.1111/1759-7714.13594
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author Choi, Yong Jun
Kim, Taehee
Kim, Eun Young
Lee, Sang Hoon
Kwon, Do Sun
Chang, Yoon Soo
author_facet Choi, Yong Jun
Kim, Taehee
Kim, Eun Young
Lee, Sang Hoon
Kwon, Do Sun
Chang, Yoon Soo
author_sort Choi, Yong Jun
collection PubMed
description BACKGROUND: Hyperprogressive disease (HPD) is a paradoxical acceleration of tumor growth after immune checkpoint inhibitor (ICI) treatment. This study aimed to identify the risk factors and to present a predictive model for HPD in patients treated with ICIs. METHODS: A total of 78 non‐small cell lung cancer (NSCLC) cases, treated with at least two cycles of ICIs who underwent computed tomography (CT) for response assessment were recruited into the study from January 2016 to August 2019. HPD was defined by the following criteria: (i) time‐to‐treatment failure <2 months; (ii) a 50% increase in the sum of target lesion diameters; (iii) new development of at least two lesions in an already involved organ; (iv) appearance of a new organ lesion; and (v) a decrease in ECOG PS 2. RESULTS: Of the 78 total patients, 15 (19.2%) had HPD. The risk factors of HPD were age; primary lesion size; and metastases in the contralateral lung, pleura, liver, and bone in multivariable logistic regression (odds ratio [OR]; 0.9038, 1.6619, 28.5913, 23.8264, 14.5711, and 20.1533, respectively, all P‐values < 0.05). By using these risk factors, we developed a prediction model for HPD and the area under the receiver operating characteristic curve of the model was 0.9556 (95% confidence interval [CI]: 0.9133–0.9978). CONCLUSIONS: HPD is relatively common and associated with a grave clinical outcome, requiring a careful monitoring in lung cancer patients treated with ICIs. Moreover, risk factors such as age, size of tumor and number of various metastatic lesions should be taken into consideration before ICI administration. KEY POINTS: SIGNIFICANT FINDINGS OF THE STUDY: Age, primary lesion size, and number of metastases are risk factors of HPD. HPD is strongly associated with poor prognosis. HPD during ICI use needs comprehensive monitoring. WHAT THIS STUDY ADDS: This is the first study to develop a prediction model. The area under the curve of the prediction model for HPD was 0.9556.
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spelling pubmed-75295592020-10-05 Prediction model for hyperprogressive disease in non‐small cell lung cancer treated with immune checkpoint inhibitors Choi, Yong Jun Kim, Taehee Kim, Eun Young Lee, Sang Hoon Kwon, Do Sun Chang, Yoon Soo Thorac Cancer Original Articles BACKGROUND: Hyperprogressive disease (HPD) is a paradoxical acceleration of tumor growth after immune checkpoint inhibitor (ICI) treatment. This study aimed to identify the risk factors and to present a predictive model for HPD in patients treated with ICIs. METHODS: A total of 78 non‐small cell lung cancer (NSCLC) cases, treated with at least two cycles of ICIs who underwent computed tomography (CT) for response assessment were recruited into the study from January 2016 to August 2019. HPD was defined by the following criteria: (i) time‐to‐treatment failure <2 months; (ii) a 50% increase in the sum of target lesion diameters; (iii) new development of at least two lesions in an already involved organ; (iv) appearance of a new organ lesion; and (v) a decrease in ECOG PS 2. RESULTS: Of the 78 total patients, 15 (19.2%) had HPD. The risk factors of HPD were age; primary lesion size; and metastases in the contralateral lung, pleura, liver, and bone in multivariable logistic regression (odds ratio [OR]; 0.9038, 1.6619, 28.5913, 23.8264, 14.5711, and 20.1533, respectively, all P‐values < 0.05). By using these risk factors, we developed a prediction model for HPD and the area under the receiver operating characteristic curve of the model was 0.9556 (95% confidence interval [CI]: 0.9133–0.9978). CONCLUSIONS: HPD is relatively common and associated with a grave clinical outcome, requiring a careful monitoring in lung cancer patients treated with ICIs. Moreover, risk factors such as age, size of tumor and number of various metastatic lesions should be taken into consideration before ICI administration. KEY POINTS: SIGNIFICANT FINDINGS OF THE STUDY: Age, primary lesion size, and number of metastases are risk factors of HPD. HPD is strongly associated with poor prognosis. HPD during ICI use needs comprehensive monitoring. WHAT THIS STUDY ADDS: This is the first study to develop a prediction model. The area under the curve of the prediction model for HPD was 0.9556. John Wiley & Sons Australia, Ltd 2020-08-11 2020-10 /pmc/articles/PMC7529559/ /pubmed/32779394 http://dx.doi.org/10.1111/1759-7714.13594 Text en © 2020 The Authors. Thoracic Cancer published by China Lung Oncology Group and John Wiley & Sons Australia, Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Articles
Choi, Yong Jun
Kim, Taehee
Kim, Eun Young
Lee, Sang Hoon
Kwon, Do Sun
Chang, Yoon Soo
Prediction model for hyperprogressive disease in non‐small cell lung cancer treated with immune checkpoint inhibitors
title Prediction model for hyperprogressive disease in non‐small cell lung cancer treated with immune checkpoint inhibitors
title_full Prediction model for hyperprogressive disease in non‐small cell lung cancer treated with immune checkpoint inhibitors
title_fullStr Prediction model for hyperprogressive disease in non‐small cell lung cancer treated with immune checkpoint inhibitors
title_full_unstemmed Prediction model for hyperprogressive disease in non‐small cell lung cancer treated with immune checkpoint inhibitors
title_short Prediction model for hyperprogressive disease in non‐small cell lung cancer treated with immune checkpoint inhibitors
title_sort prediction model for hyperprogressive disease in non‐small cell lung cancer treated with immune checkpoint inhibitors
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7529559/
https://www.ncbi.nlm.nih.gov/pubmed/32779394
http://dx.doi.org/10.1111/1759-7714.13594
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